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The exponential growth of data in recent decades has underscored the need for high-speed, real-time, and adaptive processing in machine learning. Data stream learning provides an effective framework to address this challenge. This article introduces CapyMOA, an open-source library designed specifically for data stream learning, offering powerful tools for building and deploying adaptive ML models. GitHub: https://github.com/adaptive-machine-learning/CapyMOA . Website: https://capymoa.org .

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Machine Learning for Data Streams with CapyMOA

  • 会议论文

  • 发表日期：

    2026年

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  • Yibin Sun,
  • Heitor Murilo Gomes,
  • Anton Lee,
  • Nuwan Gunasekara,
  • Guilherme Weigert Cassales,
  • Jia Justin Liu,
  • Marco Heyden,
  • Vitor Cerqueira,
  • Maroua Bahri,
  • Yun Sing Koh,
  • Bernhard Pfahringer,
  • Albert Bifet

摘要

The exponential growth of data in recent decades has underscored the need for high-speed, real-time, and adaptive processing in machine learning. Data stream learning provides an effective framework to address this challenge. This article introduces CapyMOA, an open-source library designed specifically for data stream learning, offering powerful tools for building and deploying adaptive ML models. GitHub: https://github.com/adaptive-machine-learning/CapyMOA . Website: https://capymoa.org .